AIMC Topic: Protein Conformation

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Prediction of HIV-1 protease cleavage site using a combination of sequence, structural, and physicochemical features.

BMC bioinformatics Dec 23, 2016
BACKGROUND: The human immunodeficiency virus type 1 (HIV-1) aspartic protease is an important enzyme owing to its imperative part in viral development and a causative agent of deadliest disease known as acquired immune deficiency syndrome (AIDS). Dev...
HIV-1 Algorithms HIV Infections Data Accuracy Humans HIV Protease Neural Networks, Computer Protein Conformation Computational Biology Decision Trees Amino Acid Sequence Substrate Specificity
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Predicting protein conformational changes for unbound and homology docking: learning from intrinsic and induced flexibility.

Proteins Dec 5, 2016
Predicting protein conformational changes from unbound structures or even homology models to bound structures remains a critical challenge for protein docking. Here we present a study directly addressing the challenge by reducing the dimensionality a...
Protein Binding Computational Biology Models, Statistical Proteins Software Research Design Molecular Docking Simulation Binding Sites Thermodynamics Protein Multimerization Structural Homology, Protein Benchmarking Protein Conformation Dimensional Measurement Accuracy Machine Learning
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A Graph Approach to Mining Biological Patterns in the Binding Interfaces.

Journal of computational biology : a journal of computational molecular cell biology Nov 28, 2016
Protein-RNA interactions play important roles in the biological systems. Searching for regular patterns in the Protein-RNA binding interfaces is important for understanding how protein and RNA recognize each other and bind to form a complex. Herein, ...
Humans Animals RNA Protein Conformation Binding Sites RNA-Binding Proteins Protein Interaction Domains and Motifs Support Vector Machine Molecular Docking Simulation Computer Graphics Protein Binding Proteins Amino Acid Motifs Computational Biology Data Mining
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Machine Learning Approaches for Predicting Protein Complex Similarity.

Journal of computational biology : a journal of computational molecular cell biology Oct 17, 2016
Discriminating native-like structures from false positives with high accuracy is one of the biggest challenges in protein-protein docking. While there is an agreement on the existence of a relationship between various favorable intermolecular interac...
Humans Neural Networks, Computer Machine Learning Proteins Protein Conformation Animals Molecular Docking Simulation Protein Binding
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Correcting the impact of docking pose generation error on binding affinity prediction.

BMC bioinformatics Sep 22, 2016
BACKGROUND: Pose generation error is usually quantified as the difference between the geometry of the pose generated by the docking software and that of the same molecule co-crystallised with the considered protein. Surprisingly, the impact of this e...
Pyrazines Protein Binding Humans Nuclear Proteins Ligands Transcription Factors Software Protein Conformation Molecular Docking Simulation
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Molecular Properties of Drugs Interacting with SLC22 Transporters OAT1, OAT3, OCT1, and OCT2: A Machine-Learning Approach.

The Journal of pharmacology and experimental therapeutics Aug 3, 2016
Statistical analysis was performed on physicochemical descriptors of ∼250 drugs known to interact with one or more SLC22 "drug" transporters (i.e., SLC22A6 or OAT1, SLC22A8 or OAT3, SLC22A1 or OCT1, and SLC22A2 or OCT2), followed by application of ma...
Organic Cation Transporter 1 Substrate Specificity Organic Anion Transport Protein 1 Organic Anion Transporters, Sodium-Independent Protein Binding Computational Biology Models, Molecular Membrane Transport Proteins Protein Conformation Pharmaceutical Preparations Hydrogen-Ion Concentration Machine Learning
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Adaptive local learning in sampling based motion planning for protein folding.

BMC systems biology Aug 1, 2016
BACKGROUND: Simulating protein folding motions is an important problem in computational biology. Motion planning algorithms, such as Probabilistic Roadmap Methods, have been successful in modeling the folding landscape. Probabilistic Roadmap Methods ...
Thermodynamics Movement Protein Folding Proteins Models, Molecular Machine Learning Protein Conformation Computational Biology
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A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces.

International journal of molecular sciences Jul 27, 2016
Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous publ...
Proteins Humans Databases, Protein Machine Learning Algorithms Protein Conformation Protein Interaction Mapping Computational Biology Protein Interaction Domains and Motifs
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Protease Inhibitors in View of Peptide Substrate Databases.

Journal of chemical information and modeling Jun 9, 2016
Protease substrate profiling has nowadays almost become a routine task for experimentalists, and the knowledge on protease peptide substrates is easily accessible via the MEROPS database. We present a shape-based virtual screening workflow using vROC...
User-Computer Interface Models, Molecular Drug Evaluation, Preclinical Substrate Specificity Protease Inhibitors Ligands Protein Conformation Machine Learning Peptides Small Molecule Libraries Peptide Hydrolases Databases, Pharmaceutical
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Toward High-Throughput Predictive Modeling of Protein Binding/Unbinding Kinetics.

Journal of chemical information and modeling May 20, 2016
One of the unaddressed challenges in drug discovery is that drug potency determined in vitro is not a reliable indicator of drug activity in vivo. Accumulated evidence suggests that in vivo activity is more strongly correlated with the binding/unbind...
Static Electricity Thermodynamics Protein Binding Safety Computational Biology Ligands Kinetics Machine Learning Protein Conformation Molecular Dynamics Simulation Drug Discovery
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